Determining the appropriate sample size is an important part of good clinical trial design. When there is uncertainty about some of the design parameters (e.g. variability, control rate, model parameters), it can be challenging to determine up front the number of subjects required for robust evaluation of the study objectives. The aim of this PSI one day meeting is to present an overview of available methods for sample size re-estimation together with several case studies where such methods have been used in late phase clinical trials. There will be plenty of opportunity for discussion and interaction with other statisticians working in this area. Registration is now closed. Please contact the secretariat if you wish to inquire.
There are two distinct reasons for sample size re-estimation in clinical trials: the first is to maintain power when trial data indicate the response variance has been under-estimated; the second is to adapt to interim estimates of the treatment effect. I shall explain how a combination test can be used to ensure rigorous protection of the type I error rate when sample size is adapted in the light of observed data. I shall describe methods for increasing sample size to maintain power when response variance is higher than expected, based on either blinded or unblended variance estimates. I shall discuss the relationship between trial designs that adjust sample size in response to the estimated treatment effect and group sequential designs, which start with a higher maximum sample size but stop early when the data support such a decision. In particular, I shall describe the “promising zone” approach of Mehta and Pocock (Statistics in Medicine, 2011) and show how to modify this procedure in order reduce the average sample size and achieve similar performance to an efficient group sequential design.
Simon Day
Clinical Trials Consulting &Training Ltd
Sample Size Re-Estimation – Some random observations
I was an author on one of the very early papers on sample size re-estimation (Birkett and Day, Stats in Med, 1994; 13: 2455–2463) and have since followed the field with much interest, some despair, and more than a little exasperation.This talk will illustrate some of these facets – mostly based around such methods used in a regulatory context. Several personal experiences will be included (particularly the ones that went wrong) as well as some of the approaches and myths I see in my regular consulting work. What’s “allowed” and what’s not? What makes sense and what doesn’t?
Heinz Schmidli
Novartis
Blinded sample-size re-estimation in multiple sclerosis clinical trials
Multiple sclerosis (MS) is a progressive, degenerative disease. MS is the most common disorder of the CNS in adults, affecting up to 2.5 million people worldwide. Clinical trials in MS use count, recurrent event and time-to-event primary endpoints. Methodology for blinded sample size re-estimation with such endpoints is briefly reviewed. A case study illustrates how to implement blinded sample size re-estimation in a confirmatory MS trial.
Mike Greenwood, AstraZeneca
Do we need more patients? Your statistics should be correct. Make sure you communicate effectively!
We performed a blinded estimation of the pooled exacerbation rate and shape parameter from a negative binomial model in a COPD exacerbation study. This talk will briefly cover the statistics, the practical aspects and focus on the importance of clear (and understandable to non-statisticians) communication of the results and their implications
Nikhil Chauhan, BTG International Ltd
An experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock, 2011) in a phase 3 oncology study
I will share my experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock, 2011) in a phase 3 oncology study for the purposes of obtaining a US FDA marketing approval. I will outline how we decided on using this study design, how the sample size calculation was performed, and how the promising zone boundaries were set. I will also share our experience in demonstrating the acceptability of the study design to FDA, in terms of showing control of Type I error. Reference: Mehta, CR and Pocock, SJ (2011), Adaptive increase in sample size when interim results are promising: A practical guide with examples. Statist. Med., 30: 3267–3284. doi: 10.1002/sim.4102
Blinded sample size re-estimation in a Phase III study investigating Progression Free Survival
The CLARINET study investigated the effect of lanreotide compared to placebo in the treatment of metastatic enteropancreatic neuroendocrine tumours with progression free survival as primary endpoint. We will describe the design of the study, the justification for the blinded sample-size re-estimation and some practical aspects of carrying out that decision, including communication within the company, with the DSMB and with regulatory authorities.
Pantelis Vlachos
Cytel
Sample Size Re-estimation : « De-risking » a crucial stage of clinical development
Developing cancer treatments is a high-stakes endeavor – especially for emerging biotechs and specialty pharmas with limited portfolios. Conventional phase 3 trial designs are “all or nothing” propositions and well over 50% of these pivotal studies end in failure. Unlike conventional studies, adaptive approaches allow beneficial design changes following interim analysis (IA). A Sample Size Re-estimation design allows selection of the strategy most likely to succeed. We present a case study of such an adaptive approach used to both effectively “de-risk” the final clinical stage as well as be accepted by FDA reviewers based on the concept of the “Promising Zone”. Rather than committing to a larger sample size up front, the decision is deferred until the clinical evidence justifies cost of added subjects. The strategy provided the confidence company leaders – and investors – needed to launch the final development effort toward approval.
Registration
Early Bird Rate (until 14th October 2016)
After 14th October 2016
PSI Member
£120 + VAT
£160 + VAT
Non-Member
£160 + VAT
£220 + VAT
Academic
£60 + VAT
£90 + VAT
Registration closes on 26th October 2016
Please contact the PSI secretariat on psi@mci-group.com if you have any queries.
Registration is now closed. Please contact the secretariat if you wish to inquire.
Upcoming Events
PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities
This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation.
The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication.
The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication.
The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This webinar brings together three bitesize complementary sessions to help PSI contributors create conference presentations and posters that communicate clearly and inclusively. Participants will explore how to refine their message, prepare materials effectively, and adopt practical habits that support confident, accessible delivery. A focused, supportive session designed to elevate every contribution.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
Join our Health Technology Assessment (HTA) European Special Interest Group (ESIG) for a webinar on the strategic role of statisticians in the Joint Clinical Assessment (JCA). The introduction of the JCA marks a new era for evidence generation and market access in Europe. As HTA requirements become more harmonized and methodologically demanding, the role of statisticians has evolved far beyond data analysis. Today, statistical expertise is central to shaping clinical development strategies, designing robust comparative evidence, and ensuring that submissions withstand the scrutiny of EU-level assessors. In this webinar, we explore how statisticians contribute strategically to successful JCA outcomes.
Statisticians in the Age of AI: On Route to Strategic Partnership
A 90-minute webinar featuring two case studies from Bayer and Roche demonstrating how statisticians successfully integrated into AI programs, followed by interactive discussion on strategies for elevating statistical expertise in the AI era.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
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As a Statistical Scientist at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
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Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
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Pierre Fabre - Lead Statistician- Clinical Trials M/F
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We are looking for Senior Statistical Programmers in the UK to join Veramed, where you'll deliver high-impact programming solutions in an FSP-style capacity, while advancing your career in a supportive, growth-driven environment.
